Create app.py

app.py

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+import gradio as gr
+import os
+import openai
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+# Set your API keys as environment variables or replace os.getenv with your actual keys
+DEEPSEEK_API_KEY = os.getenv("DEEPSEEK_API_KEY")
+OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
+
+# Initialize OpenAI client
+openai.api_key = OPENAI_API_KEY
+
+# Load DeepSeek model
+deepseek_model_id = "deepseek-ai/deepseek-llm-7b-chat"
+tokenizer = AutoTokenizer.from_pretrained(deepseek_model_id)
+deepseek_model = AutoModelForCausalLM.from_pretrained(
+    deepseek_model_id,
+    torch_dtype=torch.float16,
+    device_map="auto"
+)
+
+def generate_response(prompt, model_provider, temperature, top_p, max_tokens, repetition_penalty):
+    if model_provider == "DeepSeek":
+        inputs = tokenizer(prompt, return_tensors="pt").to(deepseek_model.device)
+        outputs = deepseek_model.generate(
+            **inputs,
+            do_sample=True,
+            temperature=temperature,
+            top_p=top_p,
+            max_new_tokens=max_tokens,
+            repetition_penalty=repetition_penalty
+        )
+        return tokenizer.decode(outputs[0], skip_special_tokens=True)
+    elif model_provider == "OpenAI":
+        try:
+            response = openai.ChatCompletion.create(
+                model="gpt-3.5-turbo",  # or another model of your choice
+                messages=[{"role": "user", "content": prompt}],
+                temperature=temperature,
+                top_p=top_p,
+                max_tokens=max_tokens,
+                presence_penalty=repetition_penalty
+            )
+            return response.choices[0].message["content"].strip()
+        except Exception as e:
+            return f"OpenAI API Error: {str(e)}"
+    else:
+        return "Invalid model provider selected."
+
+with gr.Blocks() as demo:
+    gr.Markdown("## 🔍 LLM Chat Interface")
+    with gr.Row():
+        model_provider = gr.Dropdown(
+            choices=["DeepSeek", "OpenAI"],
+            value="DeepSeek",
+            label="Select Model Provider"
+        )
+    prompt = gr.Textbox(label="Enter your prompt", lines=4, placeholder="Type your message here...")
+    with gr.Accordion("Advanced Settings", open=False):
+        temperature = gr.Slider(0.1, 1.5, value=0.7, step=0.1, label="Temperature")
+        top_p = gr.Slider(0.1, 1.0, value=0.9, step=0.05, label="Top-p")
+        max_tokens = gr.Slider(32, 2048, value=512, step=32, label="Max New Tokens")
+        repetition_penalty = gr.Slider(1.0, 2.0, value=1.1, step=0.1, label="Repetition Penalty")
+    output = gr.Textbox(label="Response")
+    submit = gr.Button("Generate")
+
+    submit.click(
+        fn=generate_response,
+        inputs=[prompt, model_provider, temperature, top_p, max_tokens, repetition_penalty],
+        outputs=output
+    )
+
+demo.launch()